Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary ...linear regression. However, different algorithms have rarely been compared in terms of their predictive ability.
This study compared 16 algorithms to predict annual average fine particle (PM2.5) and nitrogen dioxide (NO2) concentrations across Europe. The evaluated algorithms included linear stepwise regression, regularization techniques and machine learning methods. Air pollution models were developed based on the 2010 routine monitoring data from the AIRBASE dataset maintained by the European Environmental Agency (543 sites for PM2.5 and 2399 sites for NO2), using satellite observations, dispersion model estimates and land use variables as predictors. We compared the models by performing five-fold cross-validation (CV) and by external validation (EV) using annual average concentrations measured at 416 (PM2.5) and 1396 sites (NO2) from the ESCAPE study. We further assessed the correlations between predictions by each pair of algorithms at the ESCAPE sites.
For PM2.5, the models performed similarly across algorithms with a mean CV R2 of 0.59 and a mean EV R2 of 0.53. Generalized boosted machine, random forest and bagging performed best (CV R2~0.63; EV R2 0.58–0.61), while backward stepwise linear regression, support vector regression and artificial neural network performed less well (CV R2 0.48–0.57; EV R2 0.39–0.46). Most of the PM2.5 model predictions at ESCAPE sites were highly correlated (R2 > 0.85, with the exception of predictions from the artificial neural network). For NO2, the models performed even more similarly across different algorithms, with CV R2s ranging from 0.57 to 0.62, and EV R2s ranging from 0.49 to 0.51. The predicted concentrations from all algorithms at ESCAPE sites were highly correlated (R2 > 0.9). For both pollutants, biases were low for all models except the artificial neural network. Dispersion model estimates and satellite observations were two of the most important predictors for PM2.5 models whilst dispersion model estimates and traffic variables were most important for NO2 models in all algorithms that allow assessment of the importance of variables.
Different statistical algorithms performed similarly when modelling spatial variation in annual average air pollution concentrations using a large number of training sites.
•Multiple statistical algorithms with very different assumptions were compared.•Despite the difference in modeling frameworks, predictions among the models exhibit generally good agreement.•The use of an external evaluation dataset strengthens evaluation by cross-validation.
•Our results confirm that short-term exposures are associated with lung health outcomes.•This study extends our knowledge that lifelong exposure increase the risk of poor lung health.•Lifelong ...exposure to air pollution impact asthma attacks, rhinitis and low lung function.•Lifelong exposure to greenness increased the risk of low lung function in adulthood.
To investigate if air pollution and greenness exposure from birth till adulthood affects adult asthma, rhinitis and lung function. Methods: We analysed data from 3428 participants (mean age 28) in the RHINESSA study in Norway and Sweden. Individual mean annual residential exposures to nitrogen dioxide (NO2), particulate matter (PM10 and PM2.5), black carbon (BC), ozone (O3) and greenness (normalized difference vegetation index (NDVI)) were averaged across susceptibility windows (0–10 years, 10–18 years, lifetime, adulthood (year before study participation)) and analysed in relation to physician diagnosed asthma (ever/allergic/non-allergic), asthma attack last 12 months, current rhinitis and low lung function (lower limit of normal (LLN), z-scores of forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and FEV1/FVC below 1.64). We performed logistic regression for asthma attack, rhinitis and LLN lung function (clustered with family and study centre), and conditional logistic regression with a matched case-control design for ever/allergic/non-allergic asthma. Multivariable models were adjusted for parental asthma and education. Results: Childhood, adolescence and adult exposure to NO2, PM10 and O3 were associated with an increased risk of asthma attacks (ORs between 1.29 and 2.25), but not with physician diagnosed asthma. For rhinitis, adulthood exposures seemed to be most important. Childhood and adolescence exposures to PM2.5 and O3 were associated with lower lung function, in particular FEV1 (range ORs 2.65 to 4.21). No associations between NDVI and asthma or rhinitis were revealed, but increased NDVI was associated with lower FEV1 and FVC in all susceptibility windows (range ORs 1.39 to 1.74). Conclusions: Air pollution exposures in childhood, adolescence and adulthood were associated with increased risk of asthma attacks, rhinitis and low lung function in adulthood. Greenness was not associated with asthma or rhinitis, but was a risk factor for low lung function.
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•Sources and dynamics of harmful particles in metro systems are not well characterised.•Fine particulate matter and CO2 were measured in the entire Copenhagen Metro.•High particle ...concentrations were found despite the system’s modernity.•A closed tunnel design and carriage ventilation with tunnel air are the likely causes of the problem.•Sliding doors alone are insufficient for keeping the air clean in carriages and at stations.
The Copenhagen Metro comprises four lines, the M1, M2, M3 and M4, with 25 subterranean stations and an additional 14 stations above ground, serving ca. 80 million passengers annually. In this study we measure fine particulate matter (PM2.5) and carbon dioxide (CO2) concentrations in stations and in trains across the entire system. In partially underground lines, high PM2.5 concentrations with an average of 109 μg m−3 are found in below-ground stations. The observed correlation between PM2.5 concentration and distance between a station and a tunnel exit is attributed to ventilation via the piston effect. The piston effect via tunnel draught relief shafts was therefore found to be relatively limited. Filter samples of particulate matter are analysed using particle-induced X-ray emission and show an iron content of 88.6 % by mass which is quite different from above-ground particulate matter and consistent with particle production by train wheels, rails and brakes. The average concentration measured at the stations of a recently opened (2019) fully underground M3 closed loop line is 168 μg m−3, further demonstrating that while piston effect-driven ventilation is effective in close proximity to tunnel openings, it is relatively limited via tunnel draught relief shafts. Measurements onboard trains show even higher PM2.5 concentrations and the patterns in CO2 concentrations suggest carriage ventilation by tunnel air. Ventilation via doors during platform stops caused a drop in observed PM (and CO2) at stations, but the system is surprisingly polluted despite its recent construction. CO2 mixing ratios ranged from ambient to around 600 ppm. Measures should be taken to control PM levels using a combination of source control and increased clean air supply of the Copenhagen and other similar metro systems.
It has been suggested that air pollution may increase the risk of type 2 diabetes but data on particulate matter with diameter <2.5μm (PM2.5) are inconsistent. We examined the association between ...long-term exposure to PM2.5 and diabetes incidence.
We used the Danish Nurse Cohort with 28,731 female nurses who at recruitment in 1993 or 1999 reported information on diabetes prevalence and risk factors, and obtained data on incidence of diabetes from National Diabetes Register until 2013. We estimated annual mean concentrations of PM2.5, particulate matter with diameter <10μm (PM10), nitrogen oxides (NOx) and nitrogen dioxide (NO2) at their residence since 1990 using a dispersion model and examined the association between the 5-year running mean of pollutants and diabetes incidence using a time-varying Cox regression.
Of 24,174 nurses 1137 (4.7%) developed diabetes. We detected a significant positive association between PM2.5 and diabetes incidence (hazard ratio; 95% confidence interval: 1.11; 1.02–1.22 per interquartile range of 3.1μg/m3), and weaker associations for PM10 (1.06; 0.98–1.14 per 2.8μg/m3), NO2 (1.05; 0.99–1.12 per 7.5μg/m3), and NOx (1.01; 0.98–1.05 per 10.2μg/m3) in fully adjusted models. Associations with PM2.5 persisted in two-pollutant models. Associations with PM2.5 were significantly enhanced in never smokers (1.24; 1.09–1.42), and augmented in obese (1.25; 1.06–1.47) and subjects with myocardial infarction (1.32; 0.86–2.02), but without significant interaction.
Fine particulate matter may the most relevant pollutant for diabetes development among women, and non-smokers, obese women, and heart disease patients may be most susceptible.
•Evidence on association of PM2.5 with diabetes is inconsistent.•We linked residential PM2.5 to diabetes incidence in Danish Nurse Cohort.•We found 39% (4–86%) increased risk of diabetes per 10μg/m3 increase in PM2.5.•PM2.5 may be the most relevant pollutant for diabetes development.•Non-smokers, obese, and heart disease patients may be most susceptible.
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•Mixed-effect model predictions showed hyperlocal variation of air pollution in urban settings.•First time that UFP map has been created with measurements on all street ...segments.•Hotspot and ratio analyses revealed differences in spatial variation between BC, NO2 and UFP.•May helps policymakers by zooming into the areas of interest and adapt urban topography.•May helps epidemiologists to differentiate between the health effects of pollutants.
Hyperlocal air quality maps are becoming increasingly common, as they provide useful insights into the spatial variation and sources of air pollutants. In this study, we produced several high-resolution concentration maps to assess the spatial differences of three traffic-related pollutants, Nitrogen dioxide (NO2), Black Carbon (BC) and Ultrafine Particles (UFP), in Amsterdam, the Netherlands, and Copenhagen, Denmark. All maps were based on a mixed-effect model approach by using state-of-the-art mobile measurements conducted by Google Street View (GSV) cars, during October 2018 – March 2020, and Land-use Regression (LUR) models based on several land-use and traffic predictor variables.
We then explored the concentration ratio between the different normalised pollutants to understand possible contributing sources to the observed hyperlocal variations. The maps developed in this work reflect, (i) expected elevated pollution concentrations along busy roads, and (ii) similar concentration patterns on specific road types, e.g., motorways, for both cities. In the ratio maps, we observed a clear pattern of elevated concentrations of UFP near the airport in both cities, compared to BC and NO2.
This is the first study to produce hyperlocal maps for BC and UFP using high-quality mobile measurements. These maps are important for policymakers and health-effect studies, trying to disentangle individual effects of key air pollutants of interest (e.g., UFP).
Evidence on the association between road traffic noise and diabetes risk is sparse and inconsistent with respect to how confounding by air pollution was treated.
In this study, we aimed to examine ...whether long-term exposure to road traffic noise over 25 years is associated with incidence of diabetes, independent of air pollution.
A total of 28,731 female nurses from the Danish Nurse cohort (Formula: see text at recruitment in 1993 or 1999) were linked to the Danish National Diabetes Register with information on incidence of diabetes from 1995 until 2013. The annual mean weighted levels of 24-h average road traffic noise (Formula: see text) at nurses' residences from 1970 until 2013 were estimated with the Nord2000 method and annual mean levels of particulate matter (PM) with diameter Formula: see text and Formula: see text (Formula: see text and Formula: see text), nitrogen dioxide (Formula: see text), and nitrogen oxide (Formula: see text) with the Danish AirGIS modeling system. Cox proportional hazards regression models were used to examine the association between residential Formula: see text in four different exposure windows (1-, 5-, 10-, and 25-years) and the incidence of diabetes, adjusted for lifestyle factors and air pollutants.
Of 23,762 nurses free of diabetes at the cohort baseline, 1,158 developed diabetes during a mean follow-up of 15.2 years. We found weak positive associations between 5-y mean exposure to Formula: see text (per Formula: see text increase) and diabetes incidence in a crude model hazard ratio (HR): 1.07; 95% confidence interval (CI): 0.99, 1.12, which attenuated in a model adjusted for lifestyle factors (HR:1.04; 95% CI: 0.97, 1.12), and reached unity after additional adjustment for Formula: see text (HR: 0.99; 0.91, 1.08). In analyses by level of urbanization, we found a positive association between noise and diabetes in urban areas (HR:1.27; 95% CI: 0.98, 1.63) that was unchanged after adjusting for Formula: see text (HR: 1.25; 95% CI: 0.97, 1.62), but we found no apparent association in provincial (HR: 1.02; 95% CI: 0.88, 1.18) or rural areas (HR: 0.97; 95% CI: 0.87, 1.08).
In the nationwide cohort of Danish nurses 44 years of age and older, we found no association between long-term exposure to road traffic noise and diabetes incidence after adjustment for Formula: see text but found suggestive evidence of an association limited to urban areas. https://doi.org/10.1289/EHP4389.
With more than 60% of the land farmed, with vulnerable freshwater and marine environments, and with one of the most intensive, export-oriented livestock sectors in the world, the nitrogen (N) ...pollution pressure from Danish agriculture is severe. Consequently, a series of policy action plans have been implemented since the mid 1980s with significant effects on the surplus, efficiency and environmental loadings of N. This paper reviews the policies and actions taken and their ability to mitigate effects of reactive N (Nr) while maintaining agricultural production. In summary, the average N-surplus has been reduced from approximately 170 kg N ha−1 yr−1 to below 100 kg N ha−1 yr−1 during the past 30 yrs, while the overall N-efficiency for the agricultural sector (crop + livestock farming) has increased from around 20-30% to 40-45%, the N-leaching from the field root zone has been halved, and N losses to the aquatic and atmospheric environment have been significantly reduced. This has been achieved through a combination of approaches and measures (ranging from command and control legislation, over market-based regulation and governmental expenditure to information and voluntary action), with specific measures addressing the whole N cascade, in order to improve the quality of ground- and surface waters, and to reduce the deposition to terrestrial natural ecosystems. However, there is still a major challenge in complying with the EU Water Framework and Habitats Directives, calling for new approaches, measures and technologies to mitigate agricultural N losses and control N flows.
Ambient air pollution has been linked to stroke, but few studies have examined in detail stroke subtypes and confounding by road traffic noise, which was recently associated with stroke. Here we ...examined the association between long-term exposure to air pollution and incidence of stroke (overall, ischemic, hemorrhagic), adjusting for road traffic noise. In a nationwide Danish Nurse Cohort consisting of 23,423 nurses, recruited in 1993 or 1999, we identified 1,078 incident cases of stroke (944 ischemic and 134 hemorrhagic) up to December 31, 2014, defined as first-ever hospital contact. The full residential address histories since 1970 were obtained for each participant and the annual means of air pollutants (particulate matter with diameter < 2.5 µm and < 10 µm (PM2.5 and PM10), nitrogen dioxide (NO2), nitrogen oxides (NOx)) and road traffic noise were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals (CI)) for the associations of one-, three, and 23-year running mean of air pollutants with stroke adjusting for potential confounders and noise. In fully adjusted models, the HRs (95% CI) per interquartile range increase in one-year running mean of PM2.5 and overall, ischemic, and hemorrhagic stroke were 1.12 (1.01–1.25), 1.13 (1.01–1.26), and 1.07 (0.80–1.44), respectively, and remained unchanged after adjustment for noise. Long-term exposure to ambient PM2.5 was associated with the risk of stroke independent of road traffic noise.
Black carbon (BC), a component of fine particulate matter particles with an aerodynamic diameter
(
), may contribute to carcinogenic effects of air pollution. Until recently however, there has been ...little evidence to evaluate this hypothesis.
This study aimed to estimate the associations between long-term exposure to BC and risk of cancer. This study was conducted within the French Gazel cohort of 20,625 subjects.
We assessed exposure to BC by linking subjects' histories of residential addresses to a map of European black carbon levels in 2010 with back- and forward-extrapolation between 1989 and 2015. We used extended Cox models, with attained age as time-scale and time-varying cumulative exposure to BC, adjusted for relevant sociodemographic and lifestyle variables. To consider latency between exposure and cancer diagnosis, we implemented a 10-y lag, and as a sensitivity analysis, a lag of 2 y. To isolate the effect of BC from that of total
, we regressed BC on
and used the residuals as the exposure variable.
During the 26-y follow-up period, there were 3,711 incident cancer cases (all sites combined) and 349 incident lung cancers. Median baseline exposure in 1989 was 2.65
interquartile range (IQR): 2.23-3.33, which generally slightly decreased over time. Using 10 y as a lag-time in our models, the adjusted hazard ratio per each IQR increase of the natural log-transformed cumulative BC was 1.17 (95% confidence interval: 1.06, 1.29) for all-sites cancer combined and 1.31 (0.93, 1.83) for lung cancer. Associations with BC residuals were also positive for both outcomes. Using 2 y as a lag-time, the results were similar.
Our findings for a cohort of French adults suggest that BC may partly explain the association between
and lung cancer. Additional studies are needed to confirm our results and further disentangle the effects of BC, total
, and other constituents. https://doi.org/10.1289/EHP8719.
Cladosporium
spp. and
Alternaria
spp. spores are dominating the airspora of Denmark. Currently, little is known about the influence of climate change on the fungal spore abundance in the air. The aim ...of this study was to examine temporal changes in airborne
Alternaria
and
Cladosporium
spores over 26 years. This is the first report of long-term airborne
Cladosporium
spore occurrence in Denmark. Air spore concentrations were obtained with a Burkard volumetric spore sampler placed in Copenhagen, Denmark, during June–September, 1990–2015. The highest monthly Spore integrals (SIn) for
Alternaria
were measured in August, whereas for
Cladosporium
July SIn was nearly as high as August SIn. Average
Alternaria
seasonal spore integral (SSIn) was 8615 Spores day m
−3
, while average 3-month (July–September)
Cladosporium
SIn was 375,533 Spores day m
−3
. Despite increasing annual temperature and decreasing relative humidity, we found a decreasing trend for
Alternaria
seasonal SIn (Slope = − 277,
R
2
= 0.38,
p
< 0.05),
Alternaria
(Slope = − 31,
R
2
= 0.27,
p
< 0.05) and
Cladosporium
(Slope = − 440,
R
2
= 0.23,
p
< 0.05) annual peak concentrations. We did not find any statistically significant trends for airborne
Alternaria
seasonal characteristics and duration, and likewise for
Cladosporium
3-month SIn and peak concentration dates. Mean temperature was the main meteorological factor affecting daily spore concentrations. However, effect of meteorological parameters on daily spore concentrations was stronger for
Cladosporium
(
R
2
= 0.41) than for
Alternaria
(
R
2
= 0.21). Both genera had diurnal peaks during the day hours, earlier for
Cladosporium
(11:30–14:30) and later for
Alternaria
(15:00–19:00). Although
Alternaria
and
Cladosporium
daily concentrations were moderately correlated (Spearman’s correlation coefficient:
r
s
= 0.55,
p
< 0.05), their overall annual indices were different, which indicates different sources and different factors determining spore release. We explain temporal decreasing trends in
Alternaria
SSIn by growing urbanisation around Copenhagen and by changes in agricultural practices.
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